Running Through Travel Career Progression: Social Worlds and Active Sport Tourism
Bibliographic record
Abstract
Using social worlds as a framework, the purpose of this study was to determine the relationships between event travel career progression with travel behavior and related intentions. As such, this study has depicted the evolving behaviors and preferences of active sport tourists in an effort to improve the localized impact of events. Using previous research on social worlds and active sport event travel careers, the authors have hypothesized that differences in social worlds immersion would be present based on event participation, travel party conditions, flow-on tourism activities, and repeat/revisit intentions, as well as differences in flow-on tourism activities based on travel conditions. In partnership with a large running festival in the Midwest United States, data were collected and analyzed to test these hypotheses ( N = 2,219). The results indicated support for the hypotheses previously outlined. Theoretical contributions to the study of active sport tourism and practical implications for the management of events and destinations are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".